Andrea Gavana wrote:
>>> Scaling each axis by its standard deviation is a typical first start.
>>> Shifting and scaling the values such that they each go from 0 to 1 is
>>> another useful thing to try.
>> Ah, magnifico! Thank you Robert and Friedrich, it seems to be working
>> now...
One other thought -- core to much engineering is dimensional analysis --
you know how we like those non-dimensional number!
I think this situation is less critical, as you are interpolating, not
optimizing or something, but many interpolation methods are built on the
idea of some data points being closer than others to your point of interest.
Who is to say if a point that is 2 hours away is closer or father than
one 2 meters away? This is essentially what you are doing.
Scaling everything to the same range is a start, but then you've still
given them an implicit weighting.
An alternative to to figure out a way to non-dimensionalize your
parameters -- that *may* give you a more physically based scaling.
And you might invent the "Gavana Number" in the process ;-)
-Chris
--
Christopher Barker, Ph.D.
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